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Learning to teach is a culturally situated activity. As teachers learn, it is important to understand not only what teachers learn, but how they learn. This article describes a qualitative case study of a subset of four teachers’ learning during a professional development surrounding a plate tectonics curriculum. Using qualitative methods, this study tells the story of how the four teachers negotiated professional vision for science teaching around dilemmas that emerged throughout the professional development. By taking a sociocultural perspective on professional vision, researchers can gain insight into how and what teachers learn in professional develop- ment settings because it renders teacher learning complex and nuanced. Additionally, we argue negotiating professional vision parallels sensemak- ing. Sensemaking around science teaching includes grappling with epis- temic issues of science in addition to pedagogy and curriculum. Implications for science teacher education are discussed. Specifically, we argue learning to teach requires teachers to engage in conversations that create opportunities to “get somewhere” in relation to dilemmas they have about teaching. In this way, professional vision is an ongoing process of learning that has no endpoint or ideal articulation of teaching or science. Therefore, by framing professional vision as a process of learning we are able to push back on simplistic descriptions of teaching and science.
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Reinforcement Learning with Guarantees that Hold for Ever
Reinforcement learning is a successful explore-and-exploit approach, where a controller tries to learn how to navigate an unknown environment. The principle approach is for an intelligent agent to learn how to maximise expected rewards. But what happens if the objective refers to non-terminating systems? We can obviously not wait until an infinite amount of time has passed, assess the success, and update. But what can we do? This talk will tell.
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- PAR ID:
- 10417919
- Editor(s):
- Groote, J.F.; Huisman, M.
- Date Published:
- Journal Name:
- Formal Methods for Industrial Critical Systems. FMICS 2022
- Volume:
- 13487
- Page Range / eLocation ID:
- 3-7
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1007/978-3-031-15008-1_1
